Abstract African American (AA) women experience higher pre-menopausal breast cancer incidence and higher breast cancer mortality compared to European Americans, and the reasons for this disparity are complex. To date, there is evidence that inherited genetic variation contributes to breast cancer risk, including rare variants like BRCA as well as common polymorphisms identified by genome-wide association studies (GWAS). These loci are thought to explain less than 30% of familial breast cancer risk. With an increasing need to explore the degree to which rare and potentially population-specific variants contribute to breast cancer risk, we propose studies rooted in the study of African American families and the benefits that families can provide for rare variant mapping. The paucity of family-based investigations into the genetics of breast cancer disparities is due largely to difficulties in minority recruitment. Our community-based partnerships, tailored AA family recruitment and novel linkage findings set us apart and fill a critical gap in the literature for AA familial breast cancer research. Building on our existing resource of AA families (The Jewels in Our Genes Study) and our discovery of novel linkage peaks, we will conduct fine mapping studies under the identified linkage peaks in the largest available AA breast cancer consortia. We will also conduct a GWAS that integrates family- and population- based case control data, followed by a meta-GWAS in conjunction with AA breast cancer consortia. We specifically hypothesize that undiscovered and potentially population-specific variants lie under our linkage peaks and that a combined familial and population-based GWAS approach will enrich our ability to discover novel associations between rarer and moderately penetrant alleles and breast cancer risk. Our proposal represents highly collaborative and efficient efforts to exploit the utility of family-based methods for breast cancer gene mapping and the abundant existing GWAS data to test hypotheses that cannot be tested in the absence of AA family data. Further, our study will inform on the potential genetic overlap of familial and apparently sporadic breast cancer. In summary, we propose utilizing existing family- and population-based GWAS data in novel ways that includes consortia collaborations for large-scale genetic studies to answer important question about breast cancer disparities.